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Glut3 promotes cellular O-GlcNAcylation as a distinctive tumor-supportive feature in Treg cells

Cellular & Molecular Immunology volume 21, pages 1474–1490 (2024)Cite this article

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A Comment to this article was published on 17 December 2024

Abstract

Regulatory T cells (Tregs) establish dominant immune tolerance but obstruct tumor immune surveillance, warranting context-specific mechanistic insights into the functions of tumor-infiltrating Tregs (TIL-Tregs). We show that enhanced posttranslational O-linked N-acetylglucosamine modification (O-GlcNAcylation) of cellular factors is a molecular feature that promotes a tumor-specific gene expression signature and distinguishes TIL-Tregs from their systemic counterparts. We found that altered glucose utilization through the glucose transporter Glut3 is a major facilitator of this process. Treg-specific deletion of Glut3 abrogates tumor immune tolerance, while steady-state immune homeostasis remains largely unaffected in mice. Furthermore, by employing mouse tumor models and human clinical data, we identified the NF-κB subunit c-Rel as one such factor that, through Glut3-dependent O-GlcNAcylation, functionally orchestrates gene expression in Tregs at tumor sites. Together, these results not only identify immunometabolic alterations and molecular events contributing to fundamental aspects of Treg biology, specifically at tumor sites but also reveal tumor-specific cellular properties that can aid in the development of Treg-targeted cancer immunotherapies.

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Data availability

The RNA-seq datasets that support the findings of this study are deposited in the Gene Expression Omnibus (GEO; https://www.ncbi.nlm.nih.gov/geo/) under accession no. GSE235402.

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Acknowledgements

We thank H. Jung and H. Nam for their technical assistance in cell sorting and K. Cho for their technical assistance in confocal microscopy. We also acknowledge the assistance of Dr. Gustavo Palacios for lipidomic and metabolomic analysis. YC was financially supported by the Dissertation Completion Award of the University of Georgia and American Lebanese Syrian Associated Charities (ALSAC) at St. Jude Children’s Research Hospital. AG acknowledges support by the High Performance and Cloud Computing Group at the Zentrum für Datenverarbeitung of the University of Tübingen, the state of Baden-Württemberg through bwHPC and the German Research Foundation (DFG) through grant no INST 37/935-1 FUGG, and the de.NBI Cloud within the German Network for Bioinformatics Infrastructure (de.NBI) and ELIXIR-DE (Forschungszentrum Jülich and W-de.NBI-001, W-de.NBI-004, W-de.NBI-008, W-de.NBI-010, W-de.NBI-013, W-de.NBI-014, W-de.NBI-016, W-de.NBI-022) for supporting the computational analysis carried out in this work. AS was supported by BrainKorea21 Plus scholarship from the National Research Foundation of Korea (NRF). This research, in part, was supported by the Basic Science Research Program (grant# 4.24643.01) funded by the Ministry of Education, Korea, and NRF grants# RS-2023–00260454 (AS) and RS-2024–00345575 (SHI) funded by the Korea Ministry of Science and ICT (MSIT). DR is recipient of National Natural Science Foundation of China grant# 32470980.

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Author notes

  1. These authors contributed equally: Garima Sharma, Zhen Gao.

Authors and Affiliations

  1. Department of Life Sciences, Pohang University of Science and Technology (POSTECH), Pohang, 37673, Republic of Korea

    Amit Sharma, Garima Sharma, Chan Johng Kim, Sin-Hyeog Im & Dipayan Rudra

  2. Innovation Research Center for Biofuture Technology (B-IRC), Pohang University of Science and Technology (POSTECH), Pohang, 37673, Republic of Korea

    Amit Sharma

  3. ImmmunoBiome Inc, Pohang, 37673, Republic of Korea

    Garima Sharma & Sin-Hyeog Im

  4. School of Life Science & Technology, ShanghaiTech University, Shanghai, 201210, China

    Zhen Gao, Ke Li, Mutong Li, Menglin Wu & Dipayan Rudra

  5. Department of Biochemistry, University of Washington, Seattle, WA, 98195, USA

    Chan Johng Kim

  6. Department of Immunology, St. Jude Children’s Research Hospital, Memphis, TN, 38105, USA

    Yingjia Chen & Yongqiang Feng

  7. Institute for Bioinformatics and Medical Informatics, University of Tübingen, Sand 14, Tübingen, 72076, Germany

    Anupam Gautam

  8. International Max Planck Research School “From Molecules to Organisms”, Max Planck Institute for Biology Tübingen, Max-Planck-Ring 5, Tübingen, 72076, Germany

    Anupam Gautam

  9. Daehang Hospital, Seoul, 06699, Republic of Korea

    Hong Bae Choi

  10. Department of Surgery, Korea University College of Medicine, Seoul, 02841, Republic of Korea

    Jin Kim & Jung-Myun Kwak

  11. State Key Laboratory of Molecular Developmental Biology, Institute of Genetics and Developmental Biology Chinese Academy of Sciences, Beijing, 100101, China

    Sin Man Lam & Guanghou Shui

  12. Lipidall Technologies Company Limited, Changzhou, 213022, Jiangsu Province, China

    Sin Man Lam

  13. University of Chinese Academy of Sciences, Beijing, 100101, China

    Guanghou Shui

  14. Center for Health Science and Technology, JIS Institute of Advanced Studies and Research, JIS University, Kolkata, 700091, India

    Sandip Paul

  15. Department of Microbiology, College of Natural Sciences, Dankook University, Cheonan, 31116, Republic of Korea

    Keunsoo Kang

  16. Institute for Convergence Research and Education in Advanced Technology, Yonsei University, Seoul, 03722, Republic of Korea

    Sin-Hyeog Im

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Contributions

AS, SHI, and DR conceptualized the project and devised the project outline. AS performed most of the experiments, analyzed the data, and wrote the manuscript. Garima Sharma performed the animal tumor experiments, flow cytometry and cell sorting. ZG performed the EAE and cell transfer-induced colitis experiments. KL and ML performed the animal tumor experiments and in vitro iTreg-based metabolic flux and 13C6-labeling experiments. MW standardized and prepared the tumor-conditioned media for metabolic flux experiments. CJK processed the human tissue sections for PLA. YC performed and analyzed the metabolomic data. AG analyzed and visualized the metabolomics data. HBC, JK, and JMK provided human tumor tissue samples. SML and  Guanghou Shui performed sample preparation and LC‒MS for 13C6-labeling experiments. SP directed the analysis of metabolomic data. YF provided scientific insights and facilities for exploratory metabolomic analysis. KK performed the computational analysis of the RNA-Seq data. SHI and DR directed the project, obtained funding, and wrote the manuscript.

Corresponding authors

Correspondence to Sin-Hyeog Im or Dipayan Rudra.

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Competing interests

Garima Sharma is an employee of ImmunoBiome Inc, South Korea. SHI is the founder and major shareholder of ImmunoBiome Inc, South Korea. SML is an employee of Lipidall Technologies Company Limited, China. The authors have no conflicting financial interests.

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Sharma, A., Sharma, G., Gao, Z. et al. Glut3 promotes cellular O-GlcNAcylation as a distinctive tumor-supportive feature in Treg cells. Cell Mol Immunol 21, 1474–1490 (2024). https://doi.org/10.1038/s41423-024-01229-8

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